NetworkX node labels relative position

I am struggling with the following problem. I want to plot a circular graph of about 100 nodes where I have to manually position them, according to a classification done previously. These nodes have an assigned label which describes them, with different text lengths, and I want to put this label adjacent to the node. The following graph is what I would want to obtain (I draw the blue circle only to show that the labels are perfectly aligned at the periphery): https://i.stack.imgur.com/Qre0Z.png

So far I have only achieved to draw this:https://i.stack.imgur.com/U7bZG.png

Here is the MWE:

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

n = 7
G = nx.complete_graph(n)
node_list = sorted(G.nodes())
angle = []
angle_dict = {}
for i, node in zip(xrange(n),node_list):
    theta = 2.0*np.pi*i/n
    angle.append((np.cos(theta),np.sin(theta)))
    angle_dict[node] = theta
pos = {}
for node_i, node in enumerate(node_list):
    pos[node] = angle[node_i]

labels = {0:'zero',1:'oneone',2:'twotwo',3:'threethreethree',4:'fourfourfourfour',5:'fivefivefivefivefive',6:'sixsixsixsixsixsix'}

# figsize is intentionally set small to condense the graph
f = plt.figure(figsize=(2,2))
r = f.canvas.get_renderer()
plt.axis('equal')
nx.draw(G,pos=pos,with_labels=True)
description = nx.draw_networkx_labels(G,pos,labels=labels)
for node, t in description.items():
    t.set_rotation(angle_dict[node]*360.0/(2.0*np.pi))
plt.show()

I guess I have to add and play with

x, y = t.get_position()
bb = t.get_window_extent(renderer=r)
radius = 1.0+2.0*bb.width/r.width
t.set_position((radius*x,radius*y))

in the loop where I set the rotation of the labels. However, I don't figure out how to set it properly as well as how to avoid to crop the canvas.

In order to show the labels outside the axes, you would need to make the axes small compared to the figure, e.g. by introducing a large margin around the axes. You would also need to set the clip state of the text, such that it's not cut off by the axes.

Positioning the labels according to the width of the bounding box would require to transform the bounding box from display coodinates to data coordinates first.

Complete solution:

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

n = 7
G = nx.complete_graph(n)
node_list = sorted(G.nodes())
angle = []
angle_dict = {}
for i, node in zip(xrange(n),node_list):
    theta = 2.0*np.pi*i/n
    angle.append((np.cos(theta),np.sin(theta)))
    angle_dict[node] = theta
pos = {}
for node_i, node in enumerate(node_list):
    pos[node] = angle[node_i]

labels = {0:'zero',1:'oneone',2:'twotwo',3:'threethreethree',4:'fourfourfourfour',5:'fivefivefivefivefive',6:'sixsixsixsixsixsix'}

# figsize is intentionally set small to condense the graph
fig, ax = plt.subplots(figsize=(5,5))
margin=0.33
fig.subplots_adjust(margin, margin, 1.-margin, 1.-margin)
ax.axis('equal')

nx.draw(G,pos=pos,with_labels=True, ax=ax)
description = nx.draw_networkx_labels(G,pos,labels=labels)

r = fig.canvas.get_renderer()
trans = plt.gca().transData.inverted()
for node, t in description.items():
    bb = t.get_window_extent(renderer=r)
    bbdata = bb.transformed(trans)
    radius = 1.2+bbdata.width/2.
    position = (radius*np.cos(angle_dict[node]),radius* np.sin(angle_dict[node]))
    t.set_position(position)
    t.set_rotation(angle_dict[node]*360.0/(2.0*np.pi))
    t.set_clip_on(False)

plt.show()